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3GPP compliant 5G/6G NR NTN OFDM waveforms Develop and analyse signal processing and/or machine learning algorithms for joint channel, delay, Doppler and carrier phase estimation, remote object ranging
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-loss events undermine statistical confidence. The aim is to develop i) edge intelligence (on-turbine smart algorithms for data preprocessing), ii) resilient data movement (error-tolerant, cybersecure
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Posting Details Student Title Classification Information Quick Link https://chapman.peopleadmin.com/postings/39061 Job Number SE176424 Position Information Department or Unit Name Fowler School
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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will be as a researcher in a two-year project carried out in close collaboration with our industry partner. The goal is to develop methods for an ML-based decision support system for monitoring and fault
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mathematical theory and algorithm development as well as engineering methods that enable robust and efficient practical solutions. As society and technology evolve toward increasingly large‑scale, data‑intensive
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algorithms for behavioral cue extraction and novel approaches for the modeling people interaction, with application to medical research and affective computing. Responsibilities: Write code and develop novel
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Engineering or related fields. - A solid background in electric power systems is required, as well as experience in the development of optimization algorithms and intelligent systems. - The ability to apply
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in the Phi_Lab, led by Dr. Azeem Ahmad, and will focus on the development of advanced reconstruction algorithms and next-generation quantitative optical microscopy and tomography systems for imaging
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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Sete, Languedoc Roussillon | France | 2 days ago
recent decades. Based on time series of lagoon, hydroclimatic and catchment evolution data, analysed retrospectively and with projections to 2050, this thesis aims to determine: 1) the influence of local